Tao Yang, BSc

Accurate radiotherapy dose prediction largely depends on beam configuration, but most deep learning-based dose prediction models rely on explicit beam Angle input, which is not feasible in the early stages of planning. This study proposes a unified framework...

To develop a clinically oriented framework for patient-specific 3D dose prediction in head-and-neck radiotherapy, emphasizing DVH-consistent performance for target coverage and OAR sparing.

To investigate the feasibility and robustness of using a VQ-VAE based deep learning model for predicting daily anatomical changes in rectal cancer radiotherapy using a large-scale dataset.

Adaptive radiotherapy (ART) requires accurate and efficient delineation of the planning target volume (PTV) on daily imaging. However, conventional automatic segmentation methods rely on large-scale, high-quality annotations, while registration-based contour...